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dc.contributor.authorMacIsaac, Kenzie Daniel
dc.contributor.authorLo, Kinyui Alice
dc.contributor.authorGordon, William
dc.contributor.authorMotola, Shmulik
dc.contributor.authorMazor, Tali
dc.contributor.authorFraenkel, Ernest
dc.date.accessioned2010-08-12T19:51:46Z
dc.date.available2010-08-12T19:51:46Z
dc.date.issued2010-04
dc.date.submitted2009-09
dc.identifier.issn1553-7358
dc.identifier.issn1553-734X
dc.identifier.urihttp://hdl.handle.net/1721.1/57501
dc.description.abstractUnderstanding the mechanistic basis of transcriptional regulation has been a central focus of molecular biology since its inception. New high-throughput chromatin immunoprecipitation experiments have revealed that most regulatory proteins bind thousands of sites in mammalian genomes. However, the functional significance of these binding sites remains unclear. We present a quantitative model of transcriptional regulation that suggests the contribution of each binding site to tissue-specific gene expression depends strongly on its position relative to the transcription start site. For three cell types, we show that, by considering binding position, it is possible to predict relative expression levels between cell types with an accuracy approaching the level of agreement between different experimental platforms. Our model suggests that, for the transcription factors profiled in these cell types, a regulatory site's influence on expression falls off almost linearly with distance from the transcription start site in a 10 kilobase range. Binding to both evolutionarily conserved and non-conserved sequences contributes significantly to transcriptional regulation. Our approach also reveals the quantitative, tissue-specific role of individual proteins in activating or repressing transcription. These results suggest that regulator binding position plays a previously unappreciated role in influencing expression and blurs the classical distinction between proximal promoter and distal binding events.en_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pcbi.1000773en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/en_US
dc.sourcePLoSen_US
dc.titleA quantitative model of transcriptional regulation reveals the influence binding location on expressionen_US
dc.typeArticleen_US
dc.identifier.citationMacIsaac, Kenzie D. et al. “A Quantitative Model of Transcriptional Regulation Reveals the Influence of Binding Location on Expression.” PLoS Comput Biol 6.4 (2010): e1000773. © 2010 MacIsaac et al.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverFraenkel, Ernest
dc.contributor.mitauthorMacIsaac, Kenzie Daniel
dc.contributor.mitauthorLo, Kinyui Alice
dc.contributor.mitauthorGordon, William
dc.contributor.mitauthorMotola, Shmulik
dc.contributor.mitauthorMazor, Tali
dc.contributor.mitauthorFraenkel, Ernest
dc.relation.journalPLoS Computational Biologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsMacIsaac, Kenzie D.; Lo, Kinyui A.; Gordon, William; Motola, Shmulik; Mazor, Tali; Fraenkel, Ernesten
dc.identifier.orcidhttps://orcid.org/0000-0001-9249-8181
dspace.mitauthor.errortrue
mit.licensePUBLISHER_CCen_US


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